This is an individual assignment. Plagiarism will be dealt with according to the University
policy. Late submission will not be accepted and no extensions will be given. This is a
project where students should solve the questions independently. The lecturer is not
allowed to help you on any aspect of the assignment, and will not answer any questions
directly related to the assignment, unless they are for clarification of the questions.
Your report should provide concise and relevant answers to all questions below and the
corresponding computer outputs. It does not need to follow a formal report format. The
computer outputs should be attached as an appendix to your report. In conducting
statistical tests throughout, clearly state all relevant information, such as the null and
alternative hypotheses, the distribution you use, the level of significance, the decision rule
(critical value or p-value).
Note that the “explain” or “interpret” type questions require concise and to-the-point
answers (no more than 0.5 A4 double-spaced page), but they should be relevant and
informative. Your report should be typed or hand-written clearly on A4 pages, doublespaced
Part I: Data Details and Background (No Questions)
The file ass2.wf1 contains the US stock price (S&P 500, RP) and dividend (S&P 500, RD),
all adjusted with inflation, monthly from 1871 to 2014. The data is obtained from Robert
Shiller’s website (http://www.econ.yale.edu/~shiller/).
It is claimed that stock price is closely related with dividend in the short-run and long run.
The question as to whether the dividend has explanatory or predictive power for future
stock return is a contentious issue in finance. In this assignment, you will analyze the
relationship using the above-mentioned data set for the U.S. stock market. You may find a
section of Fabozzi book (page 199-205) useful for the background and as an example of
statistical analysis on this topic.
Since the nature of the relationship can change over time (due to structural change;
institutional changes; regulatory changes, etc), it is sensible to break the data set into
different windows. This will also show us how the short-run and long-run relationships (if
they exist) have changed over time………………………………………………